Influence of the Low-Frequency Error of the Residual Orbit on Recovering Time-Variable Gravity Field from the Satellite-To-Satellite Tracking Mission

When using the dynamic approach to recover the time-variable gravity field, the reference orbit generated by the perturbation model and the non-conservative force observed from the accelerometer should be introduced at first, and then the observation equations of the residual orbit and the residual range rate are established. This introduces a perturbation model error and instrument noise. Thus, there are low-frequency errors in the residual orbit and the residual range rate. Currently, most studies only focus on the low-frequency error of the residual range rate, neglecting the influence of the low-frequency error in the residual orbit. Therefore, under the condition of the perturbation model error and instrument noise including the constant term and 1CPR term, the low-frequency error formulas of the residual orbit and residual range rate are derived according to the characteristics of the solution of the Hill equation. Then, the influence of the low-frequency error on the residuals is analyzed by using the simulation and the real data processing respectively. In the simulation and real data processing, the accuracy of the recovered gravity field can maintain a good consistency for different arc lengths by removing the low-frequency error in the residual orbit. Finally, the time-variable gravity field model UCAS-IGG (University of Chinese Academy of Sciences-Institute of Geodesy and Geophysics) was solved from January 2005 to February 2010 by removing the low-frequency error of the residual orbit and residual range rate. Compared with the official institutions, the UCAS-IGG presents a good consistency in the estimating time-variable gravity field signal. This study demonstrates how the effect of the low-frequency error of the residual orbit should be taken into consideration when the longer arc length is used to recover a time-variable gravity field. Using a long arc length can reduce the variables of the initial state and recover the influence of the small force.

[1]  R Jastrow,et al.  Satellite Orbits. , 1961, Science.

[2]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[3]  P. Visser Low-low satellite-to-satellite tracking: a comparison between analytical linear orbit perturbation theory and numerical integration , 2005 .

[4]  Qile Zhao,et al.  DEOS Mass Transport model (DMT-1) based on GRACE satellite data: methodology and validation , 2010 .

[5]  Peiliang Xu Position and velocity perturbations for the determination of geopotential from space geodetic measurements , 2008 .

[6]  M. Cheng,et al.  Variations in the Earth's oblateness during the past 28 years , 2004 .

[7]  Byron D. Tapley,et al.  Fundamentals of Orbit Determination , 1989 .

[8]  N. G. Val’es,et al.  CNES/GRGS 10-day gravity field models (release 2) and their evaluation , 2010 .

[9]  Jeongrae Kim,et al.  Simulation study of a low-low satellite-to-satellite tracking mission , 2000 .

[10]  Olivier Francis,et al.  Tongji-Grace02s and Tongji-Grace02k: High-Precision Static GRACE-Only Global Earth's Gravity Field Models Derived by Refined Data Processing Strategies , 2018, Journal of Geophysical Research: Solid Earth.

[11]  Jing Guo,et al.  GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients , 2011 .

[12]  M. Watkins,et al.  The gravity recovery and climate experiment: Mission overview and early results , 2004 .

[13]  Leos Mervart,et al.  The celestial mechanics approach: application to data of the GRACE mission , 2010 .

[14]  Scott B. Luthcke,et al.  FAST TRACK PAPER: Tide model errors and GRACE gravimetry: towards a more realistic assessment , 2006 .

[15]  Christopher Jekeli,et al.  Precise estimation of in situ geopotential differences from GRACE low‐low satellite‐to‐satellite tracking and accelerometer data , 2006 .

[16]  Pavel Ditmar,et al.  A technique for modeling the Earth’s gravity field on the basis of satellite accelerations , 2004 .

[17]  Zhicai Luo,et al.  Impact of Different Kinematic Empirical Parameters Processing Strategies on Temporal Gravity Field Model Determination , 2018, Journal of Geophysical Research: Solid Earth.

[18]  C. Shum,et al.  On the formulation of gravitational potential difference between the GRACE satellites based on energy integral in Earth fixed frame , 2015 .

[19]  Yunzhong Shen,et al.  An improved GRACE monthly gravity field solution by modeling the non-conservative acceleration and attitude observation errors , 2016, Journal of Geodesy.

[20]  C. McCullough,et al.  Gravity field estimation for next generation satellite missions , 2017 .

[21]  Pavel Ditmar,et al.  Understanding data noise in gravity field recovery on the basis of inter-satellite ranging measurements acquired by the satellite gravimetry mission GRACE , 2012, Journal of Geodesy.

[22]  Yunzhong Shen,et al.  Monthly gravity field models derived from GRACE Level 1B data using a modified short‐arc approach , 2015 .

[23]  C. Shum,et al.  GRACE time-variable gravity field recovery using an improved energy balance approach , 2015 .

[24]  W. M. Kaula,et al.  Theory of Satellite Geodesy: Applications of Satellites to Geodesy , 2000 .

[25]  Lei Wang,et al.  Regional surface mass anomalies from GRACE KBR measurements: Application of L‐curve regularization anda priori hydrological knowledge , 2012 .

[26]  M. Watkins,et al.  Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons , 2015 .

[27]  Olivier Francis,et al.  An Optimized Short‐Arc Approach: Methodology and Application to Develop Refined Time Series of Tongji‐Grace2018 GRACE Monthly Solutions , 2019, Journal of Geophysical Research: Solid Earth.

[28]  S. Gratton,et al.  GRACE-derived surface water mass anomalies by energy integral approach: application to continental hydrology , 2011 .

[29]  Victor Zlotnicki,et al.  Time‐variable gravity from GRACE: First results , 2004 .

[30]  Roland Klees,et al.  ‘DEOS_CHAMP-01C_70’: a model of the Earth’s gravity field computed from accelerations of the CHAMP satellite , 2006 .

[31]  M. Cheng,et al.  GGM02 – An improved Earth gravity field model from GRACE , 2005 .

[32]  Srinivas Bettadpur,et al.  High‐resolution CSR GRACE RL05 mascons , 2016 .

[33]  A. Eicker,et al.  Deriving daily snapshots of the Earth's gravity field from GRACE L1B data using Kalman filtering , 2009 .

[34]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[35]  C. Reigber,et al.  Gravity field recovery from satellite tracking data , 1989 .

[36]  Qile Zhao,et al.  Improvements in the Monthly Gravity Field Solutions Through Modeling the Colored Noise in the GRACE Data , 2018, Journal of Geophysical Research: Solid Earth.

[37]  C. Jekeli The determination of gravitational potential differences from satellite-to-satellite tracking , 1999 .

[38]  Yuan Jin-hai,et al.  ORBITAL PERTURBATION DIFFERENTIAL EQUATIONS WITH NON‐LINEAR CORRECTIONS FOR CHAMP‐LIKE SATELLITE , 2017 .

[39]  Duane E. Waliser,et al.  GRACE's spatial aliasing error , 2006 .

[40]  X. Liu,et al.  Global gravity field recovery from satellite-to-satellite tracking data with the acceleration approach , 2008 .

[41]  A. Jäggi,et al.  Monthly gravity field solutions based on GRACE observations generated with the Celestial Mechanics Approach , 2012 .

[42]  Tamara Bandikova,et al.  Improvement of the GRACE star camera data based on the revision of the combination method , 2014 .

[43]  L. Mervart,et al.  The celestial mechanics approach: theoretical foundations , 2010 .

[44]  Torsten Mayer-Gürr,et al.  Gravitationsfeldbestimmung aus der Analyse kurzer Bahnbögen am Beispiel der Satellitenmissionen CHAMP und GRACE , 2008 .

[45]  Grzegorz Michalak,et al.  GFZ GRACE Level-2 Processing Standards Document for Level-2 Product Release 0005 , 2012 .

[46]  Qile Zhao,et al.  The static gravity field model DGM-1S from GRACE and GOCE data: computation, validation and an analysis of GOCE mission’s added value , 2013, Journal of Geodesy.